Study on the State Identification Model of Cardiac Neurosis Patients with Rigid-Deficiency Symptom Based on LASSO Regression
Objective:To construct a diagnostic model for cardiac neurosis with rigid-deficiency symptoms using LASSO regression combined with Nomogram.Methods:A single-center prospective study was conducted to collect the clinical data of 141 patients with cardiac neurosis.Variables included in the analysis were age,ethnicity,marriage,education,mental/physical work,BMI,traditional Chinese medicine symptoms,and the scores of Chinese medicine five-state personality,the Hamilton Anxiety Inventory-14-item scale,the Hamilton Depression Inventory-24-item scale and the Symptom Checklist-90.The influencing factors significantly associated with the diagnosis of rigid-deficiency symptoms were screened by LASSO regression,incorporated into a binary multi-factor Logistic regression analysis to construct a diagnostic model,and the model was evaluated for predictive discrimination and calibration,internally validated using 10-fold cross-validation.Finally,the model was visualized by Nomogram,and the diagnostic threshold was determined according to the ROC curve.Results:A total of 70 patients with rigid deficiency syndrome and 71 patients with non-rigid deficiency syndrome were included.The LASSO regression screened the five most significant variables associated with the diagnosis of rigid-deficiency symptoms as female,age,fatigue,belching,and Shaoyang points in the five personality states.The model AUC was 0.85 and the H-L test was 2.94(P=0.982 4),suggesting good model differentiation and calibration,and the 10-fold cross-over internal validation results suggested an AUC of 0.82.Conclusion:In this study,the diagnostic model constructed by LASSO regression combined with Nomogram can help clinicians to rapidly diagnose patients with cardiac neurosis with rigid-deficiency symptoms,but the accuracy of the results needs to be further verified by large-sample clinical studies.
万方数据
维普
